Presentation of Classical Propositional Tableaux on Program Design - PDF document

Presentation of Classical Propositional Tableaux on Program Design Premises ∗ Juan Michelini and Álvaro Tasistro Universidad ORT Uruguay michelini@ort.edu.uy , tasistro@ort.edu.uy Abstract We propose a presentation of classical propositional tableaux elaborated by application of some principles that are noteworthy in program design, namely program derivation with separation of concerns. We start by deriving from a straightforward specification an algorithm given as a set of recursive equations for computing all models of a finite set of formulae. Thereafter we discuss the employment of data structures, mainly with regard to a manual execution of the algorithm. A requirement of natural traceability and verification leads us to the trees of sets of formulae presented in [Hintikka?] and [Ben-Ari], the correctness of which is immediate after their derivation as traces of the employment of the original equations. A further improvement avoids repetition of unmodified formulae giving rise to the trees presented in [Smullyan], whose correctness is in turn guaranteed by showing that they carry the same information as the former trees. The whole development strives at avoiding gaps, both of logical and motivational nature. 1 Introduction The context in which this work presents itself is as follows. We are in the course of developing an approach based on Functional Programming to teaching Mathematics and Programming from scratch. Such approach founds itself primarily on the construction of the mathematical objects within the conceptual and notational framework of a core of the programming lan- guage Haskell 1 . As usual in Mathematics, we consider properties and relations defined on such objects and then proceed to the illative development leading to the results of interest, all of which is accomplished in natural language 2 enhanced by further convenient notation. As we see it, the approach serves the following educational purposes: To begin with, it provides a way for learning Programming in which programs are encountered from the beginning as subjects of mathematical definitions and scrutiny, which is to our mind a funda- mental and most usually neglected conception thereof 3 . On the other hand, it proposes the study of Mathematics as based on types and functions. Besides introducing an alternative interesting in itself, this prompts teachers and students to develop a fresh approach to the most fundamental mathematical mechanisms which is generally quite useful and illuminat- ing —for all of them. As a third consequence, the mathematical results and methods are, if not directly so, readily conceived as opportunities for the development of interesting pieces of software. ∗ This work was partially supported by ANII–Agencia Nacional de Investigación e Innovación, Uruguay. 1 Specifically, a λ -calculus with a system of simple types in Curry’s style plus inductive definitions, i.e. types defined by enumeration of their constructors. We refer to this language as λ h when convenient. 2 I.e. Spanish in our case. Specifically, we do not use a formal system like e.g. Constructive Type Theory for considering such option far too demanding for novice students. 3 It also conducts to introducing Programming via the principles and techniques of the functional paradigm. We do claim that this too is a feature of our method, but the corresponding discussion is far beyond the scope of this paper. licensed under Creative Commons License CC-BY Leibniz International Proceedings in Informatics Schloss Dagstuhl – Leibniz-Zentrum für Informatik, Dagstuhl Publishing, Germany

2 Presentation of Classical Propositional Tableaux on Program Design Premises We have put the preceding ideas in practice within a Software Engineering programme of studies. We begin with a course called Foundations of Computing , which introduces polymorphic, higher-order functions, and inductive types with the fundamental methods of induction and recursion in their various forms. Subsequent to Foundations of Computing there is Logic for Computing , which concerns itself essentially with the notion of formal proof —while keeping up with the general approach to Programming and Mathematics set out at the beginning. The consideration of formal proof and of formal languages of Logic serves several purposes: Firstly, it strives to further enhance the mathematical skills of the students not only by continued practice but also through theoretical reflection. Specifically, this reflection leads to the design of artificial, formal languages intended to model the natural or spontaneous mathematical practice, which provide a first bench on which to start studying issues related to formal language treatment. Prominent among these are the design of the language of First-Order Logic for capturing mathematical propositions as well as of any of the formal systems of deduction for capturing mathematical proof. On the purely syntactic side, this problem leads to considering phenomena such as name binding and the existence of multiple syntactic categories. On the semantic side, there is e.g. the fundamental question of the correctness (i.e. soundness and completeness) of the formal systems of proof. Further, there is the problem of syntactic verification and manipulation and, specifically concerning the formal systems of proof, the ultimate question is whether proofs can be developed automatically. In the case of Propositional Logic, several complete solutions to this can be studied and implemented, whereas at least a first insight can be conveyed of the undecidability of the question for First-Order Logic, which subsequently leads to the possibility of experimenting with semi-automatic methods. A further outcome of studying Formal Logic is that it allows to introduce, and experiment at least a glimpse of the ideas of programming logic , verifying compiler and generally of formal method of software construction. We insist on the practical usefulness of the language of First-Order Logic as a specification language, not only in the context of formal methods but generally in system modeling. It follows from the foregoing that we should be very much interested in making explicit methods of proof. By this we mean both general strategies for developing and fully under- standing solutions to problems, as well as manners of presenting the corresponding proofs which convey natural, concise and complete justifications of their design. Now, as it turns out, we have observed that some methods that have arisen within what could be called the science of Programming can be employed for obtaining or conveniently presenting mathem- atical results. This is to our mind a fact to be most welcome, for it exposes a unity of method between Programming and Mathematics that cannot but bring about positive outcomes for both sides, at least in as much the learning and teaching aspects are concerned. In this paper we present an example of the latter, concerning the presentation of the method of tableaux . This is a proof procedure for both propositional and predicate logic dating back to [ ? ] and [ ? ], and whose ultimate variant (termed analytic tableaux) has been introduced in [ ? ]. It is primarily presented as directed towards deriving logically valid formulae of the language in question, but it can more generally be used to establish that given sets of formulae are unsatisfiable. Indeed, in the particular case in which such set consists of only one formula, the opposite to this is derived as logically valid. We shall presently develop the method for the propositional case. Specifically, what we do is: 1. We derive the method as a set of equations —to be used as rewriting rules— from a straightforward specification, namely the one demanding the computation of the set of all models of the given set of formulas.